Safety Data Initiative Projects
Since the inception of the Safety Data Initiative (SDI), the Department of Transportation (DOT) has worked on several pilot projects that explore the possibilities of using data for safety applications. This page provides information about these projects.
Instructional videos are being produced for each tool.
DOT launched a safety challenge asking participants to come up with innovative ways to visualize data that will reveal insights into serious crashes on our roads and rail systems while improving our understanding of transportation safety. For more information, visit the Solving for Safety Submissions page or read the press release annoucing the winner.
University of Central Florida - Real-Time Crash Risk Visualization Tools for Traffic Safety Management
Real-Time Crash Risk Visualization Tools for Traffic Safety Management provides real-time crash risk visualizations using integrated tools for traffic safety evaluation and management. Focused on highway safety, the tool will integrate real-time and static data, providing predictive analytics and diagnosing real-time traffic safety conditions. With a user-centered design, the tool uses Artificial Intelligence to suggest real-time interventions and long-term countermeasures to decision makers and operators and informs the public of zip-code level safety conditions.
Through an intuitive web-based platform, Real-Time Crash Risk Visualization Tools for Traffic Safety Management users can:
• Identify potential road safety problems including potential severe crashes in real-time; and
• Evaluate real-time pro-active traffic management strategies to make data-informed intervention decisions.
Safety Insights (formerly RoadCode) helps users make smarter safety choices by unlocking driver behavior codes hidden in near misses and perceptions. This tool combines traditional crash data with connected vehicle, driver behavior, and population data along with research from the Highway Safety Manual and Crash Modification Factor Clearinghouse. With a user-centered design, the tool helps decision-makers uncover insights about safety opportunity areas, simulate potential interventions, and evaluate predicted impact.
Through an intuitive web-based platform, Safety Insights users can:
• view traffic flow, travel patterns, and near-crash events to uncover safety opportunity areas; and
• choose infrastructure solutions based on specific conditions and see predicted impacts of an intervention.
DOT’s Volpe National Transportation Systems Center ("the Volpe Center") is leading a pilot project exploring the opportunity to estimate police-reported traffic crashes in near-real time by combining crowdsourced crash data from Waze with crash data provided by the State of Maryland via the National Highway Traffic Safety Administration’s (NHTSA) Electronic Data Transfer pilot. The Volpe Center employed machine learning techniques with these datasets to train statistical models to predict crashes. In this pilot, DOT learned these models supported with Waze data produce reasonably good estimates of police-reported crashes. For more information, visit the Waze Project Summary Document page and the Frequently Asked Questions (FAQ) page. For a transcript of the video, click on Closed Captions on Youtube or navigate here for an official transcript.
The rural speed pilot seeks to understand how traffic speed in rural areas interacts with roadway characteristics to influence the likelihood of crashes. The inclusion of speed information expands upon the existing state of practice by incorporating operational data as risk variables through statistical models. The models developed over the course of the project include speed measures to quantify highway safety risk and better predict crash occurrence. This project team developed an interactive decision support tool that visualizes data results. The data contain the expected total crashes to show segment-level high-risk analysis.
The pedestrian fatalities pilot sought to understand the relationship pedestrian fatalities may have with transportation system and built environment characteristics. Two key takeaways were discovered through analysis of data from FHWA, NHTSA, the Environmental Protection Agency (EPA), and the U.S. Census Bureau. In urban areas, traffic on non-access controlled arterials was found to significantly increase pedestrian fatality risk. Traffic on other urban roadways and all roadway types in rural areas also contributed to pedestrian fatality risk, but with weaker effects. Additionally, employment density in the retail sector was strongly associated with increased pedestrian fatality risk in both urban and rural areas. Lessons learned from this pilot may be used to understand place-specific risks. The work from this project was published in the December 2018 edition of Accident Analysis & Prevention, a copy of which is available here. An interactive map of this work is available here. For a transcript of the video, click on Closed Captions on Youtube or navigate here for an official transcript.
NHTSA is experimenting with the presentation of its Fatality Analysis Reporting System (FARS) data – a nationwide census of fatal injuries suffered in motor vehicle crashes – to supplement existing data summaries on specific topical areas. NHTSA is in the process of beta testing interactive visualizations of their Traffic Safety Fact Sheets focused on speeding and pedestrians using Tableau visualization software. By creating more interactive information, the hope is to present the data in a new way that may be helpful to policy-makers and the general public. For a transcript of the video, click on Closed Captions on Youtube or navigate here for an official transcript.
2-STEP is a portable and powerful tool that enables users to quickly identify the high traffic risk locations in literally just 2 mouse clicks. It uses geo-coded multi-year statewide crash data as input, and uses a grid approach to screen the high-risk locations. This tool can be used to analyze crash data from any state or country, with minimum data format requirements. This tool was developed separately from the Safety Data Initiative.
To access the materials for this tool, click here.
This tool is developed internally at FHWA by Dr. Wei Zhang and Dr. Lin Xiao, it is freely available to any interested users. Wei Zhang, Ph. D., P.E., firstname.lastname@example.org.